In a mobile communication environment, fluctuations in amplitude and phase can take place in a propagation channel because of Rayleigh fading caused by variations in relative locations of a mobile station and a base station. Therefore, it is common for a conventional phase modulation method which transmits data (information) by carrier phase to impose data on relative phases of successive symbols by differential encoding on a transmitting side, and to make identification and decision of the data by differential detection on a receiving side.
In the differential detection, however, one bit error in a radio section causes two bit error because the data to be transmitted is modulated with the differential encoding as mentioned above. Thus, under the same SNIR (Signal to Noise and Interference power Ratio), the received error rate will increase by 3 dB from that of the coherent detection such as binary phase shift keying (BPSK).
On the other hand, although the coherent detection that decides the phase of a received signal for each data symbol by the absolute phase has highly efficient receiving characteristics, it is difficult to decide the received absolute phase in a Rayleigh fading environment.
To solve the problem, a method is proposed that insert pilot symbols into a data symbol sequence, and carries out channel estimation of the data symbols using the pilot symbols. As a pilot symbol insertion method, there are a time multiplexed pilot channel method that inserts pilot symbols between data symbols, and a parallel pilot channel method that inserts pilot symbols in parallel with data symbols.
The following references 1-3 propose a channel estimation method based on the time multiplexed pilot channel method.
Reference 1: Seiichi Sampei and Terumi Sunaga, “Rayleigh Fading Compensation for QAM in Land Mobile Radio Communication”, IEEE Trans. Vehicular Technol. VT-42, No.2, May 1993. It proposes a method of estimating and compensating for the fading distortion using pilot symbols that are inserted between data symbols at fixed intervals and have known phases. In this method, a pilot symbol is inserted at every several data symbol intervals, and the channel estimation is carried out based on the received phases of the pilot symbols. In other words, it measures the amplitude and phase of the received signal of each path of each user at the pilot symbols before and after the current data symbol section, and estimates the channel fluctuations in the data symbol section by interpolating the measured values.
Reference 2: Hidehiro Ando et.al, “Channel Estimation Filter Using Time-Multiplexed Pilot Channel for Coherent RAKE Combining in DS-CDMA”, Mobile Radio, IEICE Trans. Commun. Vol.81-B, No.7, July 1998. It proposes a method of carrying out more highly accurate channel estimation by making channel estimation using more pilot symbols.
FIG. 23 is a diagram illustrating a channel estimation method based on the reference 2. In this method, the transmission power control is carried out at every slot interval to follow instantaneous Rayleigh fluctuations. Therefore, as illustrated in FIG. 23, the amplitude (power) of the combined symbol sequence of data symbols and pilot symbols varies at every slot interval, and the phase also varies slightly due to the operation of an amplifier during transmission. Such transmission power control enables a reverse channel of the DS-CDMA (Direct Sequence CDMA) to secure the SNIR against interference signals caused by cross-correlation with other users.
The channel estimation of the data symbols is performed using pilot symbols inserted between data symbols at fixed intervals. Specifically, it is carried out by averaging (taking coherent sums of) pilot symbols (estimated complex fading envelopes) in a plurality of slots before and after the slot, to which the data symbols to be subjected to the channel estimation belong, and by obtaining a channel estimation value {tilde over (ξ)} by taking the weighted sum (weighted average) of the average values {overscore({circumflex over (ξ)})} using weighting factors α0, α1 and so on, thereby achieving highly accurate channel estimation.
Using many pilot symbols belonging to different slots enables highly accurate channel estimation. This is because in an actual mobile propagation environment, interference signals, which are generated by thermal noise (to minimize the transmission power, a noise limited environment is created particularly at cell edges), and by cross-correlation from other users, are added to the desired signal of the current channel, and the channel estimation accuracy is degraded because of the phase and amplitude of the received signal that vary at every moment due to fading. Although the pilot symbols in different slots have different power, the channel estimation error due to the power difference is less than the reduction effect by the thermal noise and interference signals caused from using pilot symbols in more slots.
The reference 2 method assumes that the channel fluctuations in each slot are small, and employs the same weighting factors α for all the data symbols in each slot to obtain the same channel estimation value {tilde over (ξ)}. This presents a problem of impairing the characteristics in high rate fading.
Reference 3, Sadayuki Abeta et.al, “Performance Comparison between Time-Multiplexed Pilot Channel and Parallel Pilot Channel for Coherent Rake Combining in DS-CDMA Mobile Radio”, IEICE Trans. Commun. Vol.81-B, No.7, July 1998. It proposes a method of achieving highly accurate channel estimation in making channel estimation of the data symbols by obtaining a channel estimation value by appropriately taking weighted sum of the pilot symbols in a plurality of slots before and after the slot, to which the current data symbols belong, using appropriate weighting factors for each data symbol in the same slot (weighting factors αm, 0,αm, 1 and so on for m-th data symbol in the slot). First to fourth embodiments in accordance with the present invention apply this scheme (see, FIG. 3).
For example, in FIG. 23, for the (m−A)-th data symbol in the n-th slot, where A is a natural number, the pilot symbols in the n-th slot are assigned a greatest weight. This is because the pilot symbols in the n-th slot are closest (in time) to the (m−A)-th data symbol, and hence best reflect the channel state when receiving the data symbols. In contrast, for the (m+B)-th data symbol in the n-th slot, where B is a natural number, the pilot symbols in the (n+1)-th slot are assigned a greatest weight. This is because the pilot symbols in the (n+1)-th slot are closest (in time) to the (m+B)-th data symbol, and hence best reflect the channel state when receiving the data symbols.
As for the parallel pilot channel method, the following reference 4 and the foregoing reference 3 disclose a channel estimation method based on the method.
Reference 4, Sadayuki Abeta et.al, “IDS/CDMA Coherent Detection System with a Suppressed Pilot Channel”, IEEE GLOBECOM '94, pp. 1622-1626, 1994. It proposes a method of estimating and compensating for the fading distortion by inserting pilot channel having known phase in parallel with and perpendicular to the data channel for transmitting data.
The channel estimation of the data symbols is carried out by averaging the pilot symbols in a section to which the target data symbol belongs, and by obtaining the channel estimation value. Thus, the channel estimation with high SNIR is achieved. By using the estimation value, the received signal in each path of each user is detected at the positions of the pilot symbols in the current data symbol section, and the amplitude and phase measurement is carried out for the signal of each path so as to estimate and compensate for the channel fluctuations in the data symbol section.
When performing the channel estimation of the data symbols in the reference 4 method, the average of the pilot symbols is calculated only within the slot including the target data symbol, and the average is made the channel estimation value.
The foregoing reference 3 proposes a method of achieving more highly accurate channel estimation by obtaining a more highly accurate channel estimation value by taking weighted sum of the pilot symbols appropriately when carrying out the channel estimation of the data symbols. This method is applied to the fifth to eighth embodiments in accordance with the present invention (see, FIG. 14).
FIG. 14 illustrates the channel estimation method disclosed by the reference 3. In FIG. 14, the channel estimation is carried out using a pilot symbol sequence parallel to the data symbol sequence. Specifically, it obtains the channel estimation value {tilde over (ξ)} by generating a plurality of pilot blocks from the pilot symbols, by averaging the pilot symbols in each of the pilot blocks, and by taking a weighted sum of the average values {overscore({circumflex over (ξ)})} using weighting factors α1, α−1 and so on, thereby achieving highly accurate channel estimation. Using many pilot symbols belonging to different slots in carrying out the channel estimation enables the highly accurate channel estimation.
To suppress the power loss, the power of the pilot symbol sequence is set less than that of the data symbol sequence. In addition, to follow the instantaneous Rayleigh fluctuations, the transmission power control is performed at every slot interval. This enables the reverse channel in the DS-CDMA to secure the SNIR against the interference signals caused by the cross-correlation from other users.
The methods disclosed in the foregoing references 3 and 4, however, use constant weighting values regardless of the fading fluctuations. This presents a problem in that when setting optimum weighting values for low rate fading fluctuations, the highly accurate channel estimation cannot be achieved in the high rate fading, whereas when setting optimum weighting values for high rate fading fluctuations, the highly accurate channel estimation cannot be achieved in the low rate fading.